AI Medical Compendium Topic:
Ligands

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Deciphering the Complexity of Ligand-Protein Recognition Pathways Using Supervised Molecular Dynamics (SuMD) Simulations.

Journal of chemical information and modeling Apr 14, 2016
Molecular recognition is a crucial issue when aiming to interpret the mechanism of known active substances as well as to develop novel active candidates. Unfortunately, simulating the binding process is still a challenging task because it requires cl...
Molecular Dynamics Simulation Supervised Machine Learning Ligands Cell Membrane Protein Conformation Protein Binding Receptors, G-Protein-Coupled
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The Virtual Screening of the Drug Protein with a Few Crystal Structures Based on the Adaboost-SVM.

Computational and mathematical methods in medicine Apr 3, 2016
Using the theory of machine learning to assist the virtual screening (VS) has been an effective plan. However, the quality of the training set may reduce because of mixing with the wrong docking poses and it will affect the screening efficiencies. To...
Protein Conformation Chemistry, Pharmaceutical Hydrogen Cathepsin K Databases, Protein Area Under Curve Ligands Crystallization Humans Computational Biology Binding Sites Software Support Vector Machine Drug Design Algorithms Combinatorial Chemistry Techniques Models, Statistical ROC Curve Reproducibility of Results Proteins Imaging, Three-Dimensional Protein Binding
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A Sequence-Based Dynamic Ensemble Learning System for Protein Ligand-Binding Site Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 3, 2015
BACKGROUND: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands...
Protein Binding Proteins Data Interpretation, Statistical Models, Chemical Ligands Machine Learning Algorithms Molecular Docking Simulation Pattern Recognition, Automated Binding Sites Protein Interaction Mapping Sequence Analysis, Protein
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Ligand-Based Virtual Screening in a Search for Novel Anti-HIV-1 Chemotypes.

Journal of chemical information and modeling Oct 9, 2015
In a search for new anti-HIV-1 chemotypes, we developed a multistep ligand-based virtual screening (VS) protocol combining machine learning (ML) methods with the privileged structures (PS) concept. In its learning step, the VS protocol was based on H...
Biological Assay HIV-1 Ligands Inhibitory Concentration 50 Anti-HIV Agents Models, Molecular Molecular Structure Drug Evaluation, Preclinical HIV Integrase Inhibitors Humans Machine Learning Cells, Cultured
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Neural-Network Scoring Functions Identify Structurally Novel Estrogen-Receptor Ligands.

Journal of chemical information and modeling Sep 4, 2015
The magnitude of the investment required to bring a drug to the market hinders medical progress, requiring hundreds of millions of dollars and years of research and development. Any innovation that improves the efficiency of the drug-discovery proces...
Estradiol Models, Biological Databases, Factual Ligands Receptors, Estrogen Computer Simulation Molecular Conformation Drug Discovery Humans Protein Binding Neural Networks, Computer
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idDock+: Integrating Machine Learning in Probabilistic Search for Protein-Protein Docking.

Journal of computational biology : a journal of computational molecular cell biology Jul 29, 2015
Predicting the three-dimensional native structures of protein dimers, a problem known as protein-protein docking, is key to understanding molecular interactions. Docking is a computationally challenging problem due to the diversity of interactions an...
Computational Biology Proteins Ligands Protein Conformation Binding Sites Protein Multimerization Machine Learning Algorithms Molecular Docking Simulation Protein Binding
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Development of 3D-QSAR Model for Acetylcholinesterase Inhibitors Using a Combination of Fingerprint, Molecular Docking, and Structure-Based Pharmacophore Approaches.

Toxicological sciences : an official journal of the Society of Toxicology Jul 21, 2015
Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligan...
Humans Artificial Intelligence Peptide Mapping Insecticides Nootropic Agents Ligands Databases, Protein Acetylcholinesterase Molecular Conformation Nerve Tissue Proteins Expert Systems Cholinesterase Inhibitors Animals Quantitative Structure-Activity Relationship Models, Molecular Molecular Docking Simulation Binding Sites GPI-Linked Proteins Catalytic Domain Imaging, Three-Dimensional Computational Biology
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The study of dual COX-2/5-LOX inhibitors by using electronic-topological approach based on data on the ligand-receptor interactions.

Journal of molecular graphics & modelling Jun 19, 2015
Structural and electronic factors influencing selective inhibition of cyclooxygenase-2 and 5-lipoxygenase (COX-2/5-LOX) were studied by using Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking, and Density Functio...
Catalytic Domain Humans Arachidonate 5-Lipoxygenase Molecular Docking Simulation Quantum Theory Neural Networks, Computer Substrate Specificity Cyclooxygenase 2 Protein Binding Lipoxygenase Inhibitors Algorithms Ligands Structure-Activity Relationship Cyclooxygenase 2 Inhibitors Molecular Structure Datasets as Topic
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Visualization and Interpretation of Support Vector Machine Activity Predictions.

Journal of chemical information and modeling Jun 2, 2015
Support vector machines (SVMs) are among the preferred machine learning algorithms for virtual compound screening and activity prediction because of their frequently observed high performance levels. However, a well-known conundrum of SVMs (and other...
Protein Kinase Inhibitors Receptors, Dopamine D2 Mitogen-Activated Protein Kinase 14 Receptor, Cannabinoid, CB2 Support Vector Machine Humans Drug Evaluation, Preclinical Software Ligands Algorithms Linear Models
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Machine-learning scoring functions for identifying native poses of ligands docked to known and novel proteins.

BMC bioinformatics Apr 17, 2015
BACKGROUND: Molecular docking is a widely-employed method in structure-based drug design. An essential component of molecular docking programs is a scoring function (SF) that can be used to identify the most stable binding pose of a ligand, when boun...
Binding Sites Humans Drug Discovery Protein Binding Artificial Intelligence Proteins Software Ligands Drug Design
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